Decision Tree Ensemble Method for Analyzing Traffic Accidents of Novice Drivers in Urban Areas
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AuthorMoral-García, Serafín; García Castellano, Francisco Javier; Mantas Ruiz, Carlos Javier; Montella, Alfonso; Abellán Mulero, Joaquín
Data miningDecision treeNovice driversRoad SafetyTraffic accidentsSeverityDecision rules
Moral-García, S.; Castellano, J.G.; Mantas, C.J.; Montella, A.; Abellán, J. Decision Tree Ensemble Method for Analyzing Traffic Accidents of Novice Drivers in Urban Areas. Entropy 2019, 21, 360. [ doi:10.3390/e21040360]
Sponsorshiphis work has been supported by the Spanish “Ministerio de Economía y Competitividad” and by “Fondo Europeo de Desarrollo Regional” (FEDER) under Project TEC2015-69496-R.
Presently, there is a critical need to analyze traffic accidents in order to mitigate their terrible economic and human impact. Most accidents occur in urban areas. Furthermore, driving experience has an important effect on accident analysis, since inexperienced drivers are more likely to suffer fatal injuries. This work studies the injury severity produced by accidents that involve inexperienced drivers in urban areas. The analysis was based on data provided by the Spanish General Traffic Directorate. The information root node variation (IRNV) method (based on decision trees) was used to get a rule set that provides useful information about the most probable causes of fatalities in accidents involving inexperienced drivers in urban areas. This may prove useful knowledge in preventing this kind of accidents and/or mitigating their consequences.